Microsoft Microsoft Certifications DP-100 Questions & Answers

• Question 201:

  You have been tasked with constructing a machine learning model that translates language text into a different language text.

  The machine learning model must be constructed and trained to learn the sequence of the.

  Recommendation: You make use of Convolutional Neural Networks (CNNs).

  Will the requirements be satisfied?

  A. Yes

  B. No

  Correct Answer: B

• Question 202:

  You have been tasked with constructing a machine learning model that translates language text into a different language text.

  The machine learning model must be constructed and trained to learn the sequence of the.

  Recommendation: You make use of Generative Adversarial Networks (GANs).

  Will the requirements be satisfied?

  A. Yes

  B. No

  Correct Answer: B

• Question 203:

  You have been tasked with constructing a machine learning model that translates language text into a different language text.

  The machine learning model must be constructed and trained to learn the sequence of the.

  Recommendation: You make use of Recurrent Neural Networks (RNNs).

  Will the requirements be satisfied?

  A. Yes

  B. No

  Correct Answer: A

• Question 204:

  You want to train a classification model using data located in a comma-separated values (CSV) file.

  The classification model will be trained via the Automated Machine Learning interface using the Classification task type.

  You have been informed that only linear models need to be assessed by the Automated Machine Learning.

  Which of the following actions should you take?

  A. You should disable deep learning.

  B. You should enable automatic featurization.

  C. You should disable automatic featurization.

  D. You should set the task type to Forecasting.

  Correct Answer: C

  Reference: https://econml.azurewebsites.net/spec/estimation/dml.html

  https://docs.microsoft.com/en-us/azure/machine-learning/how-to-use-automated-ml-for-ml-models

• Question 205:

  You are preparing to train a regression model via automated machine learning. The data available to you has features with missing values, as well as categorical features with little discrete values.

  You want to make sure that automated machine learning is configured as follows:

  missing values must be automatically imputed.

  categorical features must be encoded as part of the training task.

  Which of the following actions should you take?

  A. You should make use of the featurization parameter with the 'auto' value pair.

  B. You should make use of the featurization parameter with the 'off' value pair.

  C. You should make use of the featurization parameter with the 'on' value pair.

  D. You should make use of the featurization parameter with the 'FeaturizationConfig' value pair.

  Correct Answer: A

  Featurization str or FeaturizationConfig

  Values: 'auto' / 'off' / FeaturizationConfig

  Indicator for whether featurization step should be done automatically or not, or whether customized featurization should be used.

  Column type is automatically detected. Based on the detected column type preprocessing/featurization is done as follows:

  Categorical: Target encoding, one hot encoding, drop high cardinality categories, impute missing values.

  Numeric: Impute missing values, cluster distance, weight of evidence.

  DateTime: Several features such as day, seconds, minutes, hours etc.

  Text: Bag of words, pre-trained Word embedding, text target encoding.

  Reference:

  https://docs.microsoft.com/en-us/python/api/azureml-train-automl-client/azureml.train.automl.automlconfig.automlconfig

• Question 206:

  You have been tasked with ascertaining if two sets of data differ considerably. You will make use of Azure Machine Learning Studio to complete your task.

  You plan to perform a paired t-test.

  Which of the following are conditions that must apply to use a paired t-test? (Choose all that apply.)

  A. All scores are independent from each other.

  B. You have a matched pairs of scores.

  C. The sampling distribution of d is normal.

  D. The sampling distribution of x1- x2 is normal.

  Correct Answer: BC

  Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/test-hypothesis-using-t-test

• Question 207:

  You are in the process of carrying out feature engineering on a dataset.

  You want to add a feature to the dataset and fill the column value.

  Recommendation: You must make use of the Group Categorical Values Azure Machine Learning Studio module.

  Will the requirements be satisfied?

  A. Yes

  B. No

  Correct Answer: B

• Question 208:

  You are in the process of carrying out feature engineering on a dataset.

  You want to add a feature to the dataset and fill the column value.

  Recommendation: You must make use of the Join Data Azure Machine Learning Studio module.

  Will the requirements be satisfied?

  A. Yes

  B. No

  Correct Answer: B

• Question 209:

  This question is included in a number of questions that depicts the identical set-up. However, every question has a distinctive result. Establish if the recommendation satisfies the requirements.

  You are in the process of carrying out feature engineering on a dataset.

  You want to add a feature to the dataset and fill the column value.

  Recommendation: You must make use of the Edit Metadata Azure Machine Learning Studio module.

  Will the requirements be satisfied?

  A. Yes

  B. No

  Correct Answer: A

  Typical metadata changes might include marking columns as features.

  Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/edit-metadata https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/join-data

  https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/group-categorical-values

• Question 210:

  You need to consider the underlined segment to establish whether it is accurate.

  To improve the amount of low incidence cases in a dataset, you should make use of the SMOTE module.

  Select “No adjustment required” if the underlined segment is accurate. If the underlined segment is inaccurate, select the accurate option.

  A. No adjustment required.

  B. Remove Duplicate Rows

  C. Join Data

  D. Edit Metadata

  Correct Answer: A

  Use the SMOTE module in Azure Machine Learning Studio to increase the number of underrepresented cases in a dataset used for machine learning. SMOTE is a better way of increasing the number of rare cases than simply duplicating existing cases.

  Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/smote